
INTELLIGENT PROCESS SYSTEMS LABORATORY (IPSL)
Home to Pourkargar Research Group @ Kansas State University
WELCOME TO IPSL




We advance digital intelligence technologies designed to enhance predictive modeling, automation, optimization, and real-time decision-making for complex chemical, biological, energy, and food systems!
The research in our lab focuses on developing intelligent frameworks and the corresponding computational tools needed for
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Controlling complex process networks,
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Applied artificial intelligence in chemical, biological, and energy systems,
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Designing cyber-physical architectures for smart process manufacturing,
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Advancing system identification using machine learning and process data analytics.
Most of our work is computational, but we are intensely interested in laboratory automation to test hypotheses, validate model predictions, and design autonomous experiments.
Our research integrates process systems engineering, artificial intelligence, computational multiscale modeling, and digital twin technology to address challenging problems in chemical, material, food, and bioengineering!
CONTACT US
Office:
2017 Durland Hall, 1701A Platt St.
Manhattan, KS 66506
IPSL Advanced Computing Lab:
2056 Durland Hall
IPSL Autonomous Manufacturing Lab:
2001 Durland Hall
Tel: 785-532-5584
Email: dbpourkargar (at) ksu (dot) edu
FOLLOW OUR RESEARCH
NEWS & UPCOMING EVENTS
July 2026
Dr. Pourkargar was promoted to Associate Professor with tenure at Kansas State University.
June 2026
Dr. Pourkargar has received the NSF CAREER Award for his project titled "Digital Intelligence Architectures for Efficient and Secure Operation of Integrated Polygeneration Systems". Link
May 2026
Our paper, A Digital Twin Framework for Predictive Modeling of Liver-on-a-Chip System Dynamics with Limited Experimental Data, has been published in the Chemical Engineering Journal. Link
Our paper, A Distributed Machine Learning Approach for Cyberattack Detection in Integrated Process Systems (FrC10.1 @ Process Control Session), has been published in the Proceedings of the American Control Conference (ACC), New Orleans, LA, 2026.